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Mixed-indicators model for identifying emerging research areas

Author

Listed:
  • Hanning Guo

    (Dalian University of Technology
    School of Library and Information Science, Indiana University)

  • Scott Weingart

    (School of Library and Information Science, Indiana University)

  • Katy Börner

    (School of Library and Information Science, Indiana University)

Abstract

This study presents a mixed model that combines different indicators to describe and predict key structural and dynamic features of emerging research areas. Three indicators are combined: sudden increases in the frequency of specific words; the number and speed by which new authors are attracted to an emerging research area, and changes in the interdisciplinarity of cited references. The mixed model is applied to four emerging research areas: RNAi, Nano, h-Index, and Impact Factor research using papers published in the Proceedings of the National Academy of Sciences of the United States of America (1982–2009) and in Scientometrics (1978–2009). Results are compared in terms of strengths and temporal dynamics. Results show that the indicators are indicative of emerging areas and they exhibit interesting temporal correlations: new authors enter the area first, then the interdisciplinarity of paper references increases, then word bursts occur. All workflows are reported in a manner that supports replication and extension by others.

Suggested Citation

  • Hanning Guo & Scott Weingart & Katy Börner, 2011. "Mixed-indicators model for identifying emerging research areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 421-435, October.
    • Handle: RePEc:spr:scient:v:89:y:2011:i:1:d:10.1007_s11192-011-0433-7
    DOI: 10.1007/s11192-011-0433-7
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    References listed on IDEAS

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    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    3. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
    4. Henry Small, 2006. "Tracking and predicting growth areas in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 595-610, September.
    5. Diana Lucio-Arias & Loet Leydesdorff, 2007. "Knowledge emergence in scientific communication: from “fullerenes” to “nanotubes”," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 603-632, March.
    6. Yoshiyuki Takeda & Yuya Kajikawa, 2009. "Optics: a bibliometric approach to detect emerging research domains and intellectual bases," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(3), pages 543-558, March.
    7. Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
    8. Anthony F. J. van Raan, 2000. "On Growth, Ageing, and Fractal Differentiation of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 347-362, February.
    9. Woo Hyoung Lee, 2008. "How to identify emerging research fields using scientometrics: An example in the field of Information Security," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 503-525, September.
    10. Mee-Jean Kim, 2001. "A bibliometric analysis of physics publications in Korea, 1994-1998," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(3), pages 503-521, March.
    11. Loet Leydesdorff & Thomas Schank, 2008. "Dynamic animations of journal maps: Indicators of structural changes and interdisciplinary developments," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1810-1818, September.
    12. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
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